#!/usr/bin/env python3
"""
AI Historical Simulation Platform - Complete Demonstration

This comprehensive demonstration showcases all platform features including:
- Multi-historical figure conversations  
- Real-time interaction examples
- Educational scenario demonstrations
- Cross-temporal debates and discussions
- Performance monitoring and analytics
- Complete workflow examples

让有趣的灵魂跨越时空在当下聚首 - Let fascinating souls gather across time in the present.
"""

import asyncio
import json
import time
from datetime import datetime
from pathlib import Path
from typing import List, Dict, Any
import sys
import logging

# Add src directory to path
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))

from platform.historical_simulation_platform import HistoricalSimulationPlatform, managed_platform
from platform.session_manager import SessionManager
from platform.performance_monitor import PerformanceMonitor, managed_performance_monitor
from platform.api_server import create_development_server
from platform.web_interface import WebInterface

logger = logging.getLogger(__name__)


class CompletePlatformDemo:
    """
    Complete demonstration of the AI Historical Simulation Platform.
    
    This class provides comprehensive examples of all platform capabilities
    including educational scenarios, research applications, and entertainment uses.
    """
    
    def __init__(self):
        """Initialize the demo system."""
        self.setup_logging()
        self.demo_results = {}
        
    def setup_logging(self):
        """Setup logging for the demonstration."""
        logging.basicConfig(
            level=logging.INFO,
            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
            handlers=[
                logging.StreamHandler(),
                logging.FileHandler(f'demo_{datetime.now().strftime("%Y%m%d_%H%M%S")}.log')
            ]
        )
    
    async def run_complete_demo(self):
        """Run the complete platform demonstration."""
        print("\n" + "="*80)
        print("🏛️  AI HISTORICAL SIMULATION PLATFORM - COMPLETE DEMONSTRATION")
        print("让有趣的灵魂跨越时空在当下聚首")
        print("Let fascinating souls gather across time in the present")
        print("="*80)
        
        try:
            async with managed_performance_monitor() as performance_monitor:
                async with managed_platform(
                    hdc_dimension=5000,  # Reduced for demo speed
                    max_concurrent_sessions=500
                ) as platform:
                    
                    self.platform = platform
                    self.performance_monitor = performance_monitor
                    
                    # Record demo start
                    await performance_monitor.record_event("demo_started", "Complete platform demonstration")
                    
                    # Run all demonstration scenarios
                    await self._demo_1_platform_initialization()
                    await self._demo_2_figure_loading_and_encoding()
                    await self._demo_3_basic_conversations()
                    await self._demo_4_cross_temporal_discussions()
                    await self._demo_5_educational_scenarios()
                    await self._demo_6_research_applications()
                    await self._demo_7_concurrent_sessions()
                    await self._demo_8_performance_monitoring()
                    await self._demo_9_api_and_web_integration()
                    await self._demo_10_complete_workflows()
                    
                    # Generate final report
                    await self._generate_demo_report()
                    
                    print("\n🎯 Complete demonstration finished successfully!")
                    print("Check the generated demo report for detailed results.")
        
        except Exception as e:
            logger.error(f"Demo failed: {e}")
            print(f"❌ Demo failed: {e}")
            raise
    
    async def _demo_1_platform_initialization(self):
        """Demonstrate platform initialization and health checking."""
        print("\n🚀 DEMO 1: Platform Initialization and Health Monitoring")
        print("-" * 60)
        
        # Check platform health
        health = await self.platform.get_platform_health()
        print(f"✅ Platform Health: {'Healthy' if health.is_healthy else 'Warning'}")
        print(f"   Uptime: {health.uptime_seconds:.1f} seconds")
        print(f"   Memory Usage: {health.memory_usage_mb:.1f} MB")
        print(f"   Active Sessions: {health.active_sessions}")
        
        # Get system metrics
        metrics = await self.platform.get_system_metrics()
        print(f"\n📊 System Metrics:")
        print(f"   HDC Dimension: {metrics['system']['hdc_dimension']}")
        print(f"   Max Concurrent Sessions: {metrics['system']['max_concurrent_sessions']}")
        print(f"   Platform Initialized: {metrics['system']['is_initialized']}")
        
        self.demo_results['initialization'] = {
            'health': health.__dict__,
            'metrics_summary': {
                'hdc_dimension': metrics['system']['hdc_dimension'],
                'max_sessions': metrics['system']['max_concurrent_sessions'],
                'initialization_successful': metrics['system']['is_initialized']
            }
        }
        
        await asyncio.sleep(1)
    
    async def _demo_2_figure_loading_and_encoding(self):
        """Demonstrate historical figure loading and personality encoding."""
        print("\n🎭 DEMO 2: Historical Figure Loading and Personality Encoding")
        print("-" * 60)
        
        demo_figures = [
            "Napoleon Bonaparte",
            "William Shakespeare", 
            "Albert Einstein",
            "Leonardo da Vinci",  # Will use defaults if not found
            "Cleopatra"           # Will use defaults if not found
        ]
        
        loaded_figures = {}
        
        for figure_name in demo_figures:
            try:
                print(f"Loading {figure_name}...", end=" ")
                start_time = time.time()
                
                figure = await self.platform.load_historical_figure(figure_name)
                load_time = time.time() - start_time
                
                print(f"✅ ({load_time:.2f}s)")
                print(f"   Historical Period: {figure.historical_period}")
                print(f"   Personality Vector Shape: {figure.personality_vector.shape}")
                print(f"   Cultural Context Keys: {list(figure.cultural_context.keys())}")
                
                loaded_figures[figure_name] = {
                    'load_time': load_time,
                    'historical_period': figure.historical_period,
                    'personality_id': figure.personality_id,
                    'vector_dimension': figure.personality_vector.shape[0]
                }
                
            except Exception as e:
                print(f"⚠️  Failed: {e}")
                loaded_figures[figure_name] = {'error': str(e)}
        
        print(f"\n📈 Loading Summary: {len(loaded_figures)} figures processed")
        
        self.demo_results['figure_loading'] = loaded_figures
        
        await asyncio.sleep(1)
    
    async def _demo_3_basic_conversations(self):
        """Demonstrate basic conversations with historical figures."""
        print("\n💬 DEMO 3: Basic Conversations with Historical Figures")
        print("-" * 60)
        
        # Create demo session
        session_id = await self.platform.session_manager.create_session(
            user_id="demo_basic_conversations",
            session_metadata={"demo": "basic_conversations"}
        )
        
        # Sample conversations with different figures
        conversations = [
            ("Napoleon Bonaparte", "What was your greatest military strategy?"),
            ("Albert Einstein", "Can you explain the theory of relativity simply?"),
            ("William Shakespeare", "What inspired you to write Romeo and Juliet?"),
        ]
        
        conversation_results = {}
        
        for figure_name, question in conversations:
            try:
                print(f"\n🎯 Conversation with {figure_name}")
                print(f"❓ Question: {question}")
                
                start_time = time.time()
                response = await self.platform.generate_response(
                    session_id=session_id,
                    figure_name=figure_name,
                    user_input=question
                )
                response_time = time.time() - start_time
                
                print(f"💭 {figure_name}: {response}")
                print(f"⏱️  Response time: {response_time*1000:.1f}ms")
                
                conversation_results[figure_name] = {
                    'question': question,
                    'response': response,
                    'response_time_ms': response_time * 1000,
                    'response_length': len(response)
                }
                
            except Exception as e:
                print(f"❌ Error with {figure_name}: {e}")
                conversation_results[figure_name] = {'error': str(e)}
        
        self.demo_results['basic_conversations'] = conversation_results
        
        await asyncio.sleep(1)
    
    async def _demo_4_cross_temporal_discussions(self):
        """Demonstrate cross-temporal discussions between historical figures."""
        print("\n🌍 DEMO 4: Cross-Temporal Discussions")
        print("-" * 60)
        
        # Create cross-temporal session
        session_id = await self.platform.session_manager.create_session(
            user_id="demo_cross_temporal",
            session_metadata={"demo": "cross_temporal_discussions"}
        )
        
        # Example 1: Leadership Discussion
        print("\n🏛️  Cross-Temporal Leadership Discussion")
        print("Participants: Napoleon Bonaparte, Albert Einstein")
        print("Topic: Leadership and Innovation")
        
        leadership_conversation = await self.platform.create_cross_temporal_conversation(
            session_id=session_id,
            figure_names=["Napoleon Bonaparte", "Albert Einstein"],
            topic="What makes a great leader in times of change?",
            rounds=2
        )
        
        print("\n📜 Conversation Transcript:")
        for i, exchange in enumerate(leadership_conversation):
            print(f"\nRound {exchange['round']} - {exchange['figure']} ({exchange.get('historical_period', 'Unknown Era')}):")
            print(f"💬 {exchange['response']}")
        
        # Example 2: Creativity Discussion
        print("\n\n🎨 Cross-Temporal Creativity Discussion")
        print("Participants: William Shakespeare, Albert Einstein")
        print("Topic: The Nature of Creativity")
        
        creativity_conversation = await self.platform.create_cross_temporal_conversation(
            session_id=session_id,
            figure_names=["William Shakespeare", "Albert Einstein"],
            topic="How does creativity work? What drives innovation and artistic expression?",
            rounds=2
        )
        
        print("\n📜 Conversation Transcript:")
        for exchange in creativity_conversation:
            print(f"\nRound {exchange['round']} - {exchange['figure']}:")
            print(f"💬 {exchange['response']}")
        
        self.demo_results['cross_temporal'] = {
            'leadership_discussion': leadership_conversation,
            'creativity_discussion': creativity_conversation
        }
        
        await asyncio.sleep(1)
    
    async def _demo_5_educational_scenarios(self):
        """Demonstrate educational applications."""
        print("\n🎓 DEMO 5: Educational Scenarios")
        print("-" * 60)
        
        # Scenario 1: History Classroom
        print("\n📚 Scenario: History Classroom - The Scientific Revolution")
        
        teacher_session = await self.platform.session_manager.create_session(
            user_id="teacher_demo",
            session_metadata={"role": "teacher", "demo": "educational"}
        )
        
        # Teacher introduces the lesson
        print("\n👩‍🏫 Teacher: Today we're learning about the Scientific Revolution.")
        print("Let's ask some key figures about this period.")
        
        # Educational questions
        educational_qa = [
            ("Albert Einstein", "How did earlier scientific discoveries influence your work?"),
            ("Leonardo da Vinci", "What drove your scientific curiosity and inventions?"),
        ]
        
        educational_results = {}
        
        for figure_name, question in educational_qa:
            try:
                print(f"\n🎯 Teacher asks {figure_name}:")
                print(f"❓ {question}")
                
                response = await self.platform.generate_response(
                    session_id=teacher_session,
                    figure_name=figure_name,
                    user_input=question
                )
                
                print(f"💭 {figure_name}: {response}")
                
                educational_results[figure_name] = {
                    'question': question,
                    'response': response
                }
                
            except Exception as e:
                print(f"❌ Error: {e}")
                educational_results[figure_name] = {'error': str(e)}
        
        # Student follow-up questions
        print("\n👨‍🎓 Student Questions:")
        
        student_session = await self.platform.session_manager.create_session(
            user_id="student_demo",
            session_metadata={"role": "student", "demo": "educational"}
        )
        
        student_questions = [
            ("Albert Einstein", "What advice would you give to young scientists?"),
            ("Leonardo da Vinci", "How do you balance art and science?")
        ]
        
        for figure_name, question in student_questions:
            try:
                print(f"\n👨‍🎓 Student asks {figure_name}: {question}")
                response = await self.platform.generate_response(
                    session_id=student_session,
                    figure_name=figure_name,
                    user_input=question
                )
                print(f"💭 {figure_name}: {response}")
                
                educational_results[f"student_{figure_name}"] = {
                    'question': question,
                    'response': response
                }
            except Exception as e:
                educational_results[f"student_{figure_name}"] = {'error': str(e)}
        
        self.demo_results['educational'] = educational_results
        
        await asyncio.sleep(1)
    
    async def _demo_6_research_applications(self):
        """Demonstrate research applications."""
        print("\n🔬 DEMO 6: Research Applications")
        print("-" * 60)
        
        print("📊 Research Scenario: Comparative Leadership Analysis")
        print("Systematic questioning of historical leaders for academic research")
        
        # Create researcher session
        researcher_session = await self.platform.session_manager.create_session(
            user_id="researcher_demo",
            session_metadata={
                "role": "researcher", 
                "project": "leadership_analysis",
                "demo": "research"
            }
        )
        
        # Research questions for systematic analysis
        research_questions = [
            "What do you believe are the essential qualities of a good leader?",
            "How did you handle your greatest failure or setback?",
            "What role should emotion play in leadership decisions?",
            "How do you think leadership has changed since your time?"
        ]
        
        research_subjects = ["Napoleon Bonaparte", "Albert Einstein"]
        research_data = {}
        
        for figure_name in research_subjects:
            print(f"\n🔍 Researching {figure_name}")
            figure_data = {}
            
            for i, question in enumerate(research_questions, 1):
                try:
                    print(f"   Question {i}/4: {question[:50]}..." if len(question) > 50 else f"   Question {i}/4: {question}")
                    
                    start_time = time.time()
                    response = await self.platform.generate_response(
                        session_id=researcher_session,
                        figure_name=figure_name,
                        user_input=question
                    )
                    response_time = time.time() - start_time
                    
                    figure_data[f"Q{i}"] = {
                        'question': question,
                        'response': response,
                        'response_time': response_time,
                        'word_count': len(response.split())
                    }
                    
                    print(f"   ✅ Response received ({response_time:.2f}s, {len(response.split())} words)")
                    
                except Exception as e:
                    print(f"   ❌ Error: {e}")
                    figure_data[f"Q{i}"] = {'error': str(e)}
            
            research_data[figure_name] = figure_data
        
        # Generate research summary
        print(f"\n📊 Research Summary:")
        for figure_name, data in research_data.items():
            successful_responses = [q for q in data.values() if 'error' not in q]
            avg_response_time = sum(q.get('response_time', 0) for q in successful_responses) / len(successful_responses) if successful_responses else 0
            avg_word_count = sum(q.get('word_count', 0) for q in successful_responses) / len(successful_responses) if successful_responses else 0
            
            print(f"   {figure_name}: {len(successful_responses)}/{len(research_questions)} responses")
            print(f"      Avg response time: {avg_response_time:.2f}s")
            print(f"      Avg word count: {avg_word_count:.0f} words")
        
        self.demo_results['research'] = research_data
        
        await asyncio.sleep(1)
    
    async def _demo_7_concurrent_sessions(self):
        """Demonstrate concurrent session handling."""
        print("\n⚡ DEMO 7: Concurrent Session Handling")
        print("-" * 60)
        
        print("🔄 Testing platform with multiple simultaneous users")
        
        # Create multiple concurrent sessions
        num_concurrent = 10
        concurrent_tasks = []
        
        for i in range(num_concurrent):
            task = self._simulate_user_session(i)
            concurrent_tasks.append(task)
        
        print(f"🚀 Starting {num_concurrent} concurrent user sessions...")
        
        start_time = time.time()
        results = await asyncio.gather(*concurrent_tasks, return_exceptions=True)
        total_time = time.time() - start_time
        
        # Analyze results
        successful_sessions = [r for r in results if isinstance(r, dict) and 'error' not in r]
        failed_sessions = [r for r in results if not isinstance(r, dict) or 'error' in r]
        
        print(f"\n📊 Concurrent Session Results:")
        print(f"   Total sessions: {num_concurrent}")
        print(f"   Successful: {len(successful_sessions)}")
        print(f"   Failed: {len(failed_sessions)}")
        print(f"   Success rate: {len(successful_sessions)/num_concurrent:.1%}")
        print(f"   Total time: {total_time:.2f}s")
        print(f"   Throughput: {num_concurrent/total_time:.1f} sessions/second")
        
        if successful_sessions:
            avg_session_time = sum(s.get('total_time', 0) for s in successful_sessions) / len(successful_sessions)
            avg_response_time = sum(s.get('avg_response_time', 0) for s in successful_sessions) / len(successful_sessions)
            
            print(f"   Avg session time: {avg_session_time:.2f}s")
            print(f"   Avg response time: {avg_response_time*1000:.1f}ms")
        
        self.demo_results['concurrent_sessions'] = {
            'total_sessions': num_concurrent,
            'successful': len(successful_sessions),
            'failed': len(failed_sessions),
            'success_rate': len(successful_sessions)/num_concurrent,
            'total_time': total_time,
            'throughput': num_concurrent/total_time
        }
        
        await asyncio.sleep(1)
    
    async def _simulate_user_session(self, user_id: int) -> Dict[str, Any]:
        """Simulate a single user session for concurrent testing."""
        try:
            session_start = time.time()
            
            # Create session
            session_id = await self.platform.session_manager.create_session(
                user_id=f"concurrent_user_{user_id}",
                session_metadata={"demo": "concurrent", "user_index": user_id}
            )
            
            # Select figure
            figures = ["Napoleon Bonaparte", "Albert Einstein", "William Shakespeare"]
            figure_name = figures[user_id % len(figures)]
            
            # Generate multiple responses
            questions = [
                "What is your greatest achievement?",
                "What advice would you give to young people?",
                "How do you want to be remembered?"
            ]
            
            response_times = []
            
            for question in questions:
                response_start = time.time()
                response = await self.platform.generate_response(
                    session_id=session_id,
                    figure_name=figure_name,
                    user_input=f"{question} (User {user_id})"
                )
                response_time = time.time() - response_start
                response_times.append(response_time)
            
            total_time = time.time() - session_start
            
            # Clean up session
            await self.platform.session_manager.remove_session(session_id)
            
            return {
                'user_id': user_id,
                'figure': figure_name,
                'total_time': total_time,
                'avg_response_time': sum(response_times) / len(response_times),
                'messages_exchanged': len(questions) * 2  # questions + responses
            }
            
        except Exception as e:
            return {
                'user_id': user_id,
                'error': str(e)
            }
    
    async def _demo_8_performance_monitoring(self):
        """Demonstrate performance monitoring capabilities."""
        print("\n📊 DEMO 8: Performance Monitoring")
        print("-" * 60)
        
        # Record some test metrics
        await self.performance_monitor.record_metric("demo.test_metric", 42.0, {"demo": True})
        await self.performance_monitor.record_response_time(150.0, "demo_operation")
        await self.performance_monitor.record_event("demo_event", "Demo performance monitoring")
        
        # Get current performance metrics
        current_metrics = await self.performance_monitor.get_current_metrics()
        
        print("📈 Current Performance Metrics:")
        if current_metrics.get('response_times'):
            rt = current_metrics['response_times']
            print(f"   Response Times: avg={rt.get('avg', 0):.1f}ms, count={rt.get('count', 0)}")
        
        if current_metrics.get('system'):
            sys_metrics = current_metrics['system']
            print(f"   CPU Usage: {sys_metrics.get('cpu_percent', 0):.1f}%")
            print(f"   Memory Usage: {sys_metrics.get('memory_percent', 0):.1f}%")
            print(f"   Memory (MB): {sys_metrics.get('memory_mb', 0):.1f}")
        
        alerts = current_metrics.get('alerts', {})
        print(f"   Active Alerts: {alerts.get('active_count', 0)}")
        
        # Get comprehensive metrics
        all_metrics = await self.performance_monitor.get_all_metrics()
        
        # Generate performance report
        report = await self.performance_monitor.get_performance_report(hours=1)
        
        print(f"\n📋 Performance Report:")
        if report.get('response_time_analysis'):
            rta = report['response_time_analysis']
            print(f"   Total Requests: {rta.get('total_requests', 0)}")
            print(f"   Avg Response Time: {rta.get('avg_response_time', 0):.1f}ms")
            print(f"   Slow Requests: {rta.get('slow_requests', 0)} ({rta.get('slow_request_percentage', 0):.1f}%)")
        
        if report.get('system_analysis'):
            sa = report['system_analysis']
            print(f"   Avg CPU: {sa.get('avg_cpu_percent', 0):.1f}%")
            print(f"   Max CPU: {sa.get('max_cpu_percent', 0):.1f}%")
            print(f"   Avg Memory: {sa.get('avg_memory_percent', 0):.1f}%")
        
        performance_grade = report.get('summary', {}).get('performance_grade', 'N/A')
        print(f"   Performance Grade: {performance_grade}")
        
        self.demo_results['performance'] = {
            'current_metrics_summary': {
                'response_time_avg': current_metrics.get('response_times', {}).get('avg', 0),
                'cpu_percent': current_metrics.get('system', {}).get('cpu_percent', 0),
                'memory_percent': current_metrics.get('system', {}).get('memory_percent', 0),
                'active_alerts': alerts.get('active_count', 0)
            },
            'performance_grade': performance_grade
        }
        
        await asyncio.sleep(1)
    
    async def _demo_9_api_and_web_integration(self):
        """Demonstrate API and web interface integration."""
        print("\n🌐 DEMO 9: API and Web Interface Integration")
        print("-" * 60)
        
        try:
            # Create API server
            api_server = create_development_server(self.platform, host="127.0.0.1", port=8080)
            
            print("🔌 API Server Configuration:")
            print(f"   Host: {api_server.host}")
            print(f"   Port: {api_server.port}")
            print(f"   Admin API Key: {api_server.get_admin_api_key()}")
            
            # Create web interface
            web_interface = WebInterface(self.platform, api_server)
            
            print(f"\n🌐 Web Interface:")
            print(f"   Templates Directory: {web_interface.templates_dir}")
            print(f"   Static Files Directory: {web_interface.static_dir}")
            print(f"   Admin Credentials Available: {len(web_interface.admin_credentials)} users")
            
            # Test authentication
            auth_manager = api_server.auth_manager
            admin_key = api_server.get_admin_api_key()
            key_info = auth_manager.validate_api_key(admin_key)
            
            print(f"\n🔐 Authentication Test:")
            print(f"   API Key Valid: {'✅' if key_info else '❌'}")
            if key_info:
                print(f"   User ID: {key_info.user_id}")
                print(f"   Permissions: {', '.join(key_info.permissions)}")
                print(f"   Rate Limit: {key_info.rate_limit} req/min")
            
            # Test WebSocket manager
            ws_manager = api_server.ws_manager
            print(f"\n🔌 WebSocket Manager:")
            print(f"   Active Connections: {len(ws_manager.active_connections)}")
            print(f"   Connection Sessions: {len(ws_manager.connection_sessions)}")
            
            self.demo_results['api_web'] = {
                'api_server_configured': True,
                'web_interface_ready': True,
                'authentication_working': key_info is not None,
                'websocket_manager_ready': True,
                'admin_api_key': admin_key
            }
            
            print("✅ API and Web interface demonstration completed")
            
        except Exception as e:
            print(f"❌ API/Web integration error: {e}")
            self.demo_results['api_web'] = {'error': str(e)}
        
        await asyncio.sleep(1)
    
    async def _demo_10_complete_workflows(self):
        """Demonstrate complete end-to-end workflows."""
        print("\n🔄 DEMO 10: Complete End-to-End Workflows")
        print("-" * 60)
        
        # Workflow 1: Educational Class Session
        print("📚 Workflow 1: Complete Educational Class Session")
        
        class_workflow = await self._run_educational_workflow()
        
        # Workflow 2: Research Data Collection
        print("\n🔬 Workflow 2: Academic Research Data Collection")
        
        research_workflow = await self._run_research_workflow()
        
        # Workflow 3: Entertainment Multi-User Session
        print("\n🎭 Workflow 3: Entertainment Multi-User Session")
        
        entertainment_workflow = await self._run_entertainment_workflow()
        
        self.demo_results['workflows'] = {
            'educational': class_workflow,
            'research': research_workflow,
            'entertainment': entertainment_workflow
        }
        
        print("✅ All workflow demonstrations completed")
        
        await asyncio.sleep(1)
    
    async def _run_educational_workflow(self) -> Dict[str, Any]:
        """Run complete educational workflow."""
        workflow_start = time.time()
        
        # Step 1: Teacher preparation
        teacher_session = await self.platform.session_manager.create_session(
            user_id="teacher_workflow",
            session_metadata={"role": "teacher", "class": "world_history", "workflow": "educational"}
        )
        
        # Step 2: Load historical figures for lesson
        lesson_figures = ["Napoleon Bonaparte", "Albert Einstein"]
        for figure in lesson_figures:
            await self.platform.load_historical_figure(figure)
        
        # Step 3: Teacher asks questions
        teacher_questions = [
            ("Napoleon Bonaparte", "How did you change the political landscape of Europe?"),
            ("Albert Einstein", "How did your discoveries change our understanding of the universe?")
        ]
        
        teacher_responses = {}
        for figure, question in teacher_questions:
            response = await self.platform.generate_response(
                session_id=teacher_session,
                figure_name=figure,
                user_input=question
            )
            teacher_responses[figure] = {'question': question, 'response': response}
        
        # Step 4: Student sessions
        student_sessions = []
        for i in range(3):
            student_session = await self.platform.session_manager.create_session(
                user_id=f"student_workflow_{i}",
                session_metadata={"role": "student", "class": "world_history", "workflow": "educational"}
            )
            student_sessions.append(student_session)
        
        # Step 5: Students ask follow-up questions
        student_responses = {}
        student_questions = [
            "What challenges did you face?",
            "How do you think your work impacts us today?",
            "What advice would you give to students?"
        ]
        
        for i, student_session in enumerate(student_sessions):
            figure = lesson_figures[i % len(lesson_figures)]
            question = student_questions[i % len(student_questions)]
            
            response = await self.platform.generate_response(
                session_id=student_session,
                figure_name=figure,
                user_input=question
            )
            
            student_responses[f"student_{i}"] = {
                'figure': figure,
                'question': question,
                'response': response
            }
        
        # Step 6: Group discussion
        discussion_topic = "How do great individuals shape history?"
        group_conversation = await self.platform.create_cross_temporal_conversation(
            session_id=teacher_session,
            figure_names=lesson_figures,
            topic=discussion_topic,
            rounds=2
        )
        
        workflow_time = time.time() - workflow_start
        
        return {
            'workflow_time': workflow_time,
            'participants': len(student_sessions) + 1,  # students + teacher
            'figures_involved': lesson_figures,
            'teacher_responses': len(teacher_responses),
            'student_responses': len(student_responses),
            'group_discussion_exchanges': len(group_conversation),
            'total_interactions': len(teacher_responses) + len(student_responses) + len(group_conversation)
        }
    
    async def _run_research_workflow(self) -> Dict[str, Any]:
        """Run complete research workflow."""
        workflow_start = time.time()
        
        # Research project: Leadership styles analysis
        researcher_session = await self.platform.session_manager.create_session(
            user_id="researcher_workflow",
            session_metadata={
                "role": "researcher",
                "project": "leadership_styles_analysis",
                "workflow": "research"
            }
        )
        
        # Research subjects
        research_subjects = ["Napoleon Bonaparte", "Albert Einstein"]
        
        # Systematic data collection
        research_protocol = [
            "What was your approach to making difficult decisions?",
            "How did you motivate others to follow your vision?",
            "What do you consider your greatest leadership success?",
            "What leadership mistakes did you learn from?",
            "How did you adapt your leadership style to different situations?"
        ]
        
        research_data = {}
        
        for subject in research_subjects:
            subject_data = {}
            
            for question in research_protocol:
                response = await self.platform.generate_response(
                    session_id=researcher_session,
                    figure_name=subject,
                    user_input=question
                )
                
                subject_data[question] = {
                    'response': response,
                    'word_count': len(response.split()),
                    'timestamp': datetime.now().isoformat()
                }
            
            research_data[subject] = subject_data
        
        # Comparative analysis through cross-temporal discussion
        comparison_topics = [
            "Leadership in times of crisis",
            "Balancing confidence with humility"
        ]
        
        comparative_discussions = {}
        
        for topic in comparison_topics:
            discussion = await self.platform.create_cross_temporal_conversation(
                session_id=researcher_session,
                figure_names=research_subjects,
                topic=topic,
                rounds=2
            )
            comparative_discussions[topic] = discussion
        
        workflow_time = time.time() - workflow_start
        
        return {
            'workflow_time': workflow_time,
            'research_subjects': len(research_subjects),
            'protocol_questions': len(research_protocol),
            'total_responses': len(research_subjects) * len(research_protocol),
            'comparative_discussions': len(comparative_discussions),
            'data_points_collected': sum(len(data) for data in research_data.values())
        }
    
    async def _run_entertainment_workflow(self) -> Dict[str, Any]:
        """Run complete entertainment workflow."""
        workflow_start = time.time()
        
        # Multi-user entertainment session
        entertainment_sessions = []
        
        # Create multiple user sessions
        for i in range(4):
            session = await self.platform.session_manager.create_session(
                user_id=f"entertainment_user_{i}",
                session_metadata={"role": "user", "purpose": "entertainment", "workflow": "entertainment"}
            )
            entertainment_sessions.append(session)
        
        # Load entertaining historical figures
        entertainment_figures = ["William Shakespeare", "Napoleon Bonaparte", "Albert Einstein"]
        for figure in entertainment_figures:
            await self.platform.load_historical_figure(figure)
        
        # Users ask fun questions
        fun_interactions = {}
        
        entertaining_questions = [
            ("William Shakespeare", "Write me a short poem about modern technology"),
            ("Napoleon Bonaparte", "What would you think of social media?"),
            ("Albert Einstein", "Would you have enjoyed video games?"),
            ("William Shakespeare", "What would you tweet about?")
        ]
        
        for i, (figure, question) in enumerate(entertaining_questions):
            session = entertainment_sessions[i % len(entertainment_sessions)]
            
            response = await self.platform.generate_response(
                session_id=session,
                figure_name=figure,
                user_input=question
            )
            
            fun_interactions[f"interaction_{i}"] = {
                'user': f"entertainment_user_{i % len(entertainment_sessions)}",
                'figure': figure,
                'question': question,
                'response': response
            }
        
        # Create a fun cross-temporal conversation
        party_topic = "If you could have dinner together, what would you talk about?"
        party_conversation = await self.platform.create_cross_temporal_conversation(
            session_id=entertainment_sessions[0],
            figure_names=entertainment_figures,
            topic=party_topic,
            rounds=2
        )
        
        workflow_time = time.time() - workflow_start
        
        return {
            'workflow_time': workflow_time,
            'users': len(entertainment_sessions),
            'figures': len(entertainment_figures),
            'fun_interactions': len(fun_interactions),
            'party_conversation_exchanges': len(party_conversation),
            'total_entertainment_value': len(fun_interactions) + len(party_conversation)
        }
    
    async def _generate_demo_report(self):
        """Generate comprehensive demo report."""
        print("\n📄 Generating Demo Report...")
        
        # Get final platform metrics
        final_health = await self.platform.get_platform_health()
        final_metrics = await self.platform.get_system_metrics()
        performance_report = await self.performance_monitor.get_performance_report(hours=1)
        
        # Compile comprehensive report
        demo_report = {
            'demo_metadata': {
                'timestamp': datetime.now().isoformat(),
                'platform_version': '1.0.0',
                'demo_duration': None,  # Will be calculated
                'demo_scenarios_completed': len(self.demo_results)
            },
            'platform_health': {
                'final_health': final_health.__dict__,
                'is_healthy': final_health.is_healthy,
                'uptime_seconds': final_health.uptime_seconds
            },
            'performance_summary': {
                'grade': performance_report.get('summary', {}).get('performance_grade', 'N/A'),
                'total_figures_loaded': final_metrics['figures']['loaded'],
                'total_conversations': final_metrics['figures']['total_conversations'],
                'avg_response_quality': final_metrics['figures']['avg_quality']
            },
            'demo_scenarios': self.demo_results,
            'recommendations': performance_report.get('summary', {}).get('recommendations', [])
        }
        
        # Save report to file
        report_filename = f"platform_demo_report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
        
        with open(report_filename, 'w') as f:
            json.dump(demo_report, f, indent=2, default=str)
        
        print(f"✅ Demo report saved to: {report_filename}")
        
        # Print summary
        print(f"\n📊 DEMO SUMMARY")
        print(f"   Scenarios Completed: {len(self.demo_results)}")
        print(f"   Platform Health: {'✅ Healthy' if final_health.is_healthy else '⚠️ Warning'}")
        print(f"   Performance Grade: {performance_report.get('summary', {}).get('performance_grade', 'N/A')}")
        print(f"   Total Figures Loaded: {final_metrics['figures']['loaded']}")
        print(f"   Total Conversations: {final_metrics['figures']['total_conversations']}")
        print(f"   Platform Uptime: {final_health.uptime_seconds:.1f}s")


async def main():
    """Main demo execution function."""
    print("🎬 Starting Complete AI Historical Simulation Platform Demo")
    
    demo = CompletePlatformDemo()
    
    try:
        await demo.run_complete_demo()
        print("\n🎉 Demo completed successfully!")
        print("Check the generated report file for detailed results.")
        
    except KeyboardInterrupt:
        print("\n⏹️  Demo interrupted by user")
    except Exception as e:
        print(f"\n❌ Demo failed with error: {e}")
        logger.exception("Demo execution failed")
        raise


if __name__ == "__main__":
    asyncio.run(main())